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    Area of Science:

    • Optics and Photonics
    • Computer Vision
    • Metrology

    Background:

    • Phase-shifting profilometry is a key technique for 3D shape measurement.
    • Shadows in captured images introduce significant errors in 3D reconstruction.
    • Current methods struggle to effectively mitigate shadow-induced inaccuracies.

    Purpose of the Study:

    • To develop a novel method for removing shadow areas in 3D shape measurement.
    • To enhance the accuracy and reliability of phase-shifting profilometry systems.
    • To address the limitations of existing shadow removal techniques.

    Main Methods:

    • A new shadow detection algorithm is proposed based on mapping 3D reconstructed points to the digital micro-mirror device (DMD) plane.
    • The system is calibrated, and the object is reconstructed in 3D.
    • Shadow points are identified using a set of defined rules based on their DMD positions.

    Main Results:

    • Experimental results demonstrate the effectiveness of the proposed shadow removal method.
    • The technique successfully identifies and excludes shadow points from the 3D measurement process.
    • Significant reduction in measurement errors caused by shadows was observed.

    Conclusions:

    • The proposed method effectively removes shadow areas, improving 3D measurement accuracy in phase-shifting profilometry.
    • Mapping 3D data to the DMD provides a robust approach for shadow point detection.
    • This technique offers a valuable solution for enhancing the performance of 3D shape measurement systems.